Dr Nikolaos Argyris

BSc (Aristotle), MSc PhD (LSE)

  • Senior Lecturer in Operational Research

Expertise: decision analysis; fairness in resource allocation; multi-dimensional inequality; emergency management

Nikolaos (Nikos) Argyris is Lecturer in Operational Research at Loughborough Business School. He completed his undergraduate studies in Economics at Aristotle University, followed by an MSc and a PhD in Operational Research at the London School of Economics.

Prior to joining Loughborough, Nikos was a Research Fellow in the Department of Statistics at the University of Warwick. Previously to that he held post-doctoral positions at the London School of Economics.

Nikos has been actively involved in practical operational research projects throughout his career. Most recently as part of a team working with Public Health England on studying different modes of presenting geographical uncertainty to support decisions in radiological emergencies. While, at the LSE he was part of a team supporting resource allocation in the NHS using participative decision analysis. During his PhD he collaborated with the (former) Department for Education and Skills to develop methods to measure the efficiency of schools in England.

Nikos’ research interests broadly lie in the interface and applications of Mathematical Optimisation, Decision Theory/Analysis and Economics. My work draws together decision theory and optimisation methods to design frameworks for decision support and the underlying computational models. I am particularly interested in modelling preferences, values and objectives to support decision making.

Another interest is in fair allocation of resources, particularly in the public sector but also in the context of cost/profit sharing. I am interested in how axiomatic rules for distributive justice can be combined with preferences and used to build decision support frameworks, especially based on optimisation.

Most recently I have become interested in the measurement of Social Welfare based on several dimensions (e.g. health, wealth), particularly using a multi-dimensional stochastic dominance framework.

Journal articles


French, S, Argyris, N, Layton, H, Smith, J, Haywood, S, Hort, M (2016) Presenting Uncertain Information in Radiological Emergencies, ADMLC/2014/01, Atmospheric Dispersion Modelling Liaison Committee.